In one example embodiment, a computer-implemented method includes receiving data representing a motion plan of the autonomous vehicle via a plurality of control lanes configured to implement the motion plan to control a motion of the autonomous vehicle, the plurality of control lanes including at least a first control lane and a second control lane, and controlling the first control lane to implement the motion plan. The method includes detecting one or more faults associated with implementation of the motion plan by the first control lane or the second control lane, or in generation of the motion plan, and in response to one or more faults, controlling the first control lane or the second control lane to adjust the motion of the autonomous vehicle based at least in part on one or more fault reaction parameters associated with the one or more faults.
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1. An autonomous vehicle control system comprising: one or more processors; and one or more tangible, non-transitory, computer readable media that store instructions that when executed by the one or more processors cause the autonomous vehicle control system to perform operations, the operations comprising: receiving motion planning data for a vehicle; determining a first control lane of a plurality of control lanes for implementing a motion plan based on the motion planning data, wherein the plurality of control lanes comprise at least the first control lane and a second control lane different than the first control lane, wherein the first control lane is connected with a first set of vehicle actuation systems corresponding to the first control lane, wherein the second control lane is connected with a second set of vehicle actuation systems corresponding to the second control lane, wherein the first set of vehicle actuation systems comprise at least one first actuation system that is not present in the second set of vehicle actuation systems; determining one or more conditions associated with the vehicle; and controlling the first control lane or the second control lane to adjust a motion of the vehicle based at least in part on the one or more conditions.
An autonomous vehicle control system manages vehicle motion by dynamically selecting between multiple control lanes, each connected to distinct sets of actuation systems. The system receives motion planning data and determines which control lane to activate based on vehicle conditions. Each control lane is linked to a specific set of actuation systems, with at least one actuation system unique to each lane. For example, the first control lane may include a steering system not present in the second control lane, while the second control lane may include a braking system not present in the first. The system monitors vehicle conditions, such as speed, environment, or system status, and selects the appropriate control lane to adjust the vehicle's motion accordingly. This modular approach allows the system to adapt to different driving scenarios by leveraging the most suitable actuation systems for the current conditions, improving safety and efficiency. The system ensures seamless transitions between control lanes to maintain continuous and stable vehicle operation.
2. The autonomous vehicle control system of claim 1 , wherein the vehicle comprises a ground-based autonomous vehicle.
The invention relates to an autonomous vehicle control system designed for ground-based autonomous vehicles, such as self-driving cars, trucks, or other autonomous ground transportation systems. The system addresses the challenge of ensuring safe and efficient navigation in dynamic environments by integrating advanced perception, decision-making, and control mechanisms. The control system processes sensor data from multiple sources, including cameras, lidar, radar, and other environmental sensors, to generate a real-time understanding of the vehicle's surroundings. This data is used to detect and classify obstacles, road conditions, traffic signals, and other relevant elements in the vehicle's path. The system then applies machine learning algorithms and rule-based logic to determine optimal navigation paths, avoiding collisions and adhering to traffic regulations. Additionally, the control system includes predictive modeling to anticipate the movements of other vehicles, pedestrians, and obstacles, enabling proactive decision-making. It also incorporates adaptive control mechanisms to adjust vehicle speed, steering, and braking in response to changing conditions, ensuring smooth and safe operation. The system may further communicate with external infrastructure, such as traffic management systems or other autonomous vehicles, to enhance coordination and efficiency. By leveraging these technologies, the control system enables ground-based autonomous vehicles to operate reliably in complex environments, reducing the need for human intervention while improving safety and performance.
3. The autonomous vehicle control system of claim 2 , wherein the ground-based autonomous vehicle comprises an autonomous truck.
Autonomous vehicle control systems are used to manage the navigation and operation of self-driving vehicles, including trucks, to improve efficiency and safety. A key challenge in such systems is ensuring reliable and adaptive control, particularly for ground-based autonomous vehicles like trucks, which operate in dynamic environments with varying road conditions, traffic, and payload requirements. This invention describes an autonomous vehicle control system specifically designed for ground-based autonomous vehicles, such as trucks. The system includes a perception module that collects and processes sensor data from the vehicle's surroundings, including cameras, lidar, radar, and other sensors, to detect obstacles, road conditions, and traffic. The system also features a planning module that generates a navigation path and control commands based on the perceived environment, taking into account factors like vehicle dynamics, payload weight, and road regulations. Additionally, the system incorporates a decision-making module that adjusts the vehicle's speed, steering, and braking in real-time to ensure safe and efficient operation. The control system is optimized for autonomous trucks, which often operate in long-haul or logistics environments where precise control and adaptability are critical. The system may also include redundancy and fail-safe mechanisms to handle unexpected situations, such as sensor failures or adverse weather conditions, ensuring continuous and reliable operation. This invention enhances the autonomy and safety of ground-based autonomous vehicles, particularly trucks, by integrating advanced perception, planning, and decision-making capabilities.
4. The autonomous vehicle control system of claim 1 , wherein the motion planning data is indicative of a vehicle trajectory, and wherein controlling the first control lane or the second control lane to adjust the motion of the vehicle comprises: controlling the first control lane or the second control lane to: generate one or more vehicle control signals to track the vehicle trajectory; and provide the one or more vehicle control signals to at least one of the first set of vehicle actuation systems or at least one of the second set of vehicle actuation systems.
An autonomous vehicle control system manages vehicle motion by generating and executing motion planning data to follow a predefined vehicle trajectory. The system includes multiple control lanes, each responsible for generating vehicle control signals to adjust the vehicle's motion. These control lanes operate independently or in coordination to ensure the vehicle follows the planned trajectory accurately. The motion planning data specifies the desired vehicle trajectory, and the control lanes generate corresponding control signals to track this trajectory. These signals are then provided to the vehicle's actuation systems, such as steering, braking, or acceleration systems, to execute the planned motion. The system ensures redundancy and reliability by allowing either the first or second control lane to generate and transmit the necessary control signals, ensuring continuous and precise trajectory tracking even if one control lane fails. This approach enhances the safety and efficiency of autonomous vehicle operation by maintaining consistent motion control.
5. The autonomous vehicle control system of claim 1 , wherein the motion planning data is indicative of a vehicle trajectory, and wherein controlling the first control lane or the second control lane to adjust the motion of the vehicle comprises: controlling the first control lane to: generate one or more first vehicle control signals to track at least a first portion of the vehicle trajectory; and provide the one or more first vehicle control signals to at least one of the first set of vehicle actuation systems; and controlling the second control lane to: generate one or more second vehicle control signals to track at least a second portion of the vehicle trajectory; and provide the one or more second vehicle control signals to at least one of the second set of vehicle actuation systems.
Autonomous vehicle control systems manage vehicle motion by processing sensor data and generating control signals for actuation systems. A challenge in such systems is ensuring reliable and redundant control to maintain vehicle safety and performance, especially in the event of a failure in one control path. This invention addresses this by implementing a dual-lane control architecture where two independent control lanes operate in parallel to adjust vehicle motion based on motion planning data. The system includes a first control lane and a second control lane, each connected to separate sets of vehicle actuation systems. The motion planning data defines a vehicle trajectory, which is divided into portions for each control lane. The first control lane generates and provides control signals to track a first portion of the trajectory, while the second control lane generates and provides control signals to track a second portion. This division allows both lanes to contribute to vehicle motion control, enhancing redundancy and fault tolerance. If one lane fails, the other can continue operating, ensuring continued vehicle control. The system ensures seamless coordination between the lanes to maintain trajectory tracking accuracy and vehicle stability. This approach improves the reliability and safety of autonomous vehicle operations by leveraging redundant control pathways.
6. The autonomous vehicle control system of claim 1 , wherein the first set of vehicle actuation systems comprise: a first powertrain control system comprising one or more propulsion actuators for a propulsion or an acceleration of the vehicle; a first steering control system comprising one or more steering actuators for the vehicle; and a first braking control system comprising one or more braking actuators for the vehicle.
Autonomous vehicles require precise control of multiple systems to navigate safely and efficiently. Existing autonomous vehicle control systems often lack integrated management of propulsion, steering, and braking, leading to suboptimal performance and safety risks. This invention addresses the need for a unified control system that coordinates these critical functions. The system includes a first set of vehicle actuation systems, which are essential for autonomous operation. These systems comprise a powertrain control system with propulsion actuators for vehicle acceleration, a steering control system with actuators for directional control, and a braking control system with actuators for deceleration. Each subsystem operates in tandem to ensure smooth, coordinated vehicle movement. The powertrain control system adjusts propulsion to maintain desired speed, while the steering control system manages steering actuators to navigate turns and obstacles. The braking control system engages braking actuators to slow or stop the vehicle as needed. By integrating these systems, the invention enables precise, real-time adjustments to vehicle dynamics, enhancing safety and efficiency in autonomous driving. This approach improves responsiveness and reduces the risk of conflicts between control systems, ensuring reliable autonomous operation.
7. The autonomous vehicle control system of claim 6 , wherein the second set of vehicle actuation systems comprise: a second steering control system comprising one or more steering actuators for the vehicle; and a second braking control system comprising one or more braking actuators for the vehicle.
Autonomous vehicle control systems manage vehicle operations without human intervention, but ensuring reliable and redundant control mechanisms is critical for safety. This invention addresses the need for a robust backup control system in autonomous vehicles by providing a secondary set of vehicle actuation systems. The system includes a second steering control system with one or more steering actuators to independently control vehicle direction, and a second braking control system with one or more braking actuators to independently control vehicle deceleration. These redundant systems operate in parallel with primary control systems, ensuring continued functionality if the primary systems fail. The secondary steering and braking systems are designed to maintain vehicle stability and safety by providing independent control over steering and braking functions. This redundancy enhances fault tolerance, allowing the vehicle to respond to critical situations even if primary systems are compromised. The invention improves autonomous vehicle safety by ensuring that essential control functions remain operational under adverse conditions.
8. The autonomous vehicle control system of claim 7 , wherein the first steering actuators function independently of the second steering actuators, and wherein the first braking actuators function independently of the second braking actuators.
Autonomous vehicles require robust control systems to ensure safe and reliable operation, particularly in scenarios where redundancy is critical. A prior art system addresses this by implementing a control architecture with redundant steering and braking actuators. The system includes a primary set of steering actuators and a secondary set of steering actuators, each capable of independently controlling the vehicle's steering. Similarly, the system includes primary and secondary braking actuators, each capable of independently controlling the vehicle's braking. The independent operation of these actuator sets ensures that if one set fails, the other can continue functioning, maintaining vehicle control and safety. This redundancy is particularly valuable in autonomous driving, where system failures could lead to hazardous situations. The system may also include sensors and controllers that monitor actuator performance and switch between primary and secondary actuators as needed. By decoupling the operation of the steering and braking actuators, the system enhances fault tolerance and reliability, reducing the risk of catastrophic failures. This approach is useful in autonomous vehicles where high availability and safety are paramount.
9. The autonomous vehicle control system of claim 1 , wherein the first control lane is associated with a first capability based, at least in part, on the first set of vehicle actuation systems, wherein the second control lane is associated with a second capability based, at least in part, on the second set of vehicle actuation systems, and wherein the first capability is different than the second capability.
Autonomous vehicle control systems manage vehicle operations through multiple control lanes, each handling distinct functions. A control lane is a dedicated processing path for specific vehicle tasks, such as steering, braking, or acceleration, using a set of vehicle actuation systems. The invention addresses the need for specialized control lanes to optimize performance based on the capabilities of the actuation systems they manage. Each control lane is assigned a unique capability derived from its associated actuation systems. For example, one control lane may prioritize precise steering adjustments using advanced steering actuators, while another may focus on rapid braking responses using high-performance brake systems. The capabilities of these lanes differ because their actuation systems have distinct operational characteristics. This differentiation ensures that each control lane operates within its optimal performance range, improving overall vehicle safety and efficiency. The system dynamically assigns tasks to the appropriate control lane based on the required capability, ensuring seamless and efficient vehicle operation. This approach enhances reliability by isolating critical functions and preventing system-wide failures from affecting unrelated operations. The invention is particularly useful in autonomous vehicles where precise and adaptive control is essential for navigating complex environments.
10. The autonomous vehicle control system of claim 9 , wherein the one or more conditions are associated with one or more reaction parameters, and wherein controlling the first control lane or the second control lane to adjust the motion of the vehicle based at least in part on the one or more conditions comprises: controlling the first control lane or the second control lane to adjust the motion of the vehicle based at least in part on the one or more reaction parameters associated with the one or more conditions, wherein the one or more reaction parameters are indicative of a first reduction in the first capability or a second reduction in the second capability in response to the one or more conditions.
An autonomous vehicle control system manages vehicle motion by adjusting control lanes based on detected conditions and associated reaction parameters. The system monitors vehicle capabilities, such as sensor performance or actuator functionality, and identifies conditions that may impair these capabilities. When a condition is detected, the system adjusts the vehicle's motion by modifying control inputs to one or more control lanes—such as steering, braking, or acceleration systems—based on reaction parameters linked to the condition. These reaction parameters quantify the expected reduction in capability due to the condition, allowing the system to compensate accordingly. For example, if a sensor's accuracy degrades, the reaction parameters may dictate a reduction in speed or an increase in safety margins to maintain safe operation. The system dynamically adapts control strategies to mitigate the impact of degraded capabilities, ensuring continued safe and efficient vehicle operation under varying conditions. This approach enhances reliability by proactively adjusting control inputs in response to real-time performance changes.
11. The autonomous vehicle control system of claim 1 , wherein the autonomous vehicle control system is on-board the vehicle.
An autonomous vehicle control system is designed to manage the operation of a self-driving vehicle by processing sensor data, making navigation decisions, and controlling vehicle movements. The system addresses challenges in real-time decision-making, obstacle avoidance, and safe navigation in dynamic environments. This particular system is integrated directly into the vehicle, eliminating reliance on external infrastructure or remote servers for critical functions. By operating on-board, the system ensures low-latency responses, enhanced reliability, and the ability to function in areas with limited connectivity. The on-board design also improves data security by minimizing external communication requirements. The system may include components for sensor fusion, path planning, and vehicle actuation, all optimized for real-time performance. This approach enhances the vehicle's ability to navigate complex scenarios independently, reducing dependence on external systems and improving overall autonomy. The on-board configuration ensures that the vehicle can operate effectively in various conditions, from urban traffic to remote locations, while maintaining safety and efficiency.
12. An autonomous vehicle comprising: a plurality of actuators configured to implement one or more vehicle control signals to control a motion of the autonomous vehicle; and a vehicle control system, wherein the vehicle control system comprises: one or more processors; and one or more tangible, non-transitory, computer readable media that store instructions that when executed by the one or more processors cause the vehicle control system to perform operations, the operations comprising: receiving motion planning data for the autonomous vehicle; determining a first control lane of a plurality of control lanes for implementing a motion plan based on the motion planning data, wherein the plurality of control lanes comprise at least the first control lane and a second control lane different than the first control lane, wherein the first control lane is connected with a first set of the plurality of actuators corresponding to the first control lane, wherein the second control lane is connected with a second set of the plurality of actuators corresponding to the second control lane, wherein the first set of actuators comprise at least one first actuator ion system that is not present in the second set of actuators; determining one or more conditions associated with the autonomous vehicle; and controlling the first control lane or the second control lane to adjust the motion of the autonomous vehicle based at least in part on the one or more conditions.
Autonomous vehicles require precise control systems to manage motion and navigation. A key challenge is ensuring reliable and adaptable control over vehicle actuators to implement motion plans while accounting for varying conditions. This invention addresses this by introducing a vehicle control system with multiple control lanes, each connected to distinct sets of actuators. The system receives motion planning data and selects a control lane based on the motion plan. Each control lane is linked to a specific set of actuators, with at least one actuator in the first control lane not present in the second. The system also evaluates vehicle conditions, such as sensor data or environmental factors, and dynamically adjusts control by activating the appropriate control lane. This modular approach enhances redundancy and adaptability, allowing the vehicle to maintain safe and efficient operation under different scenarios. The invention improves fault tolerance and control flexibility by isolating actuator groups and enabling condition-based lane selection.
13. The autonomous vehicle of claim 12 , wherein the autonomous vehicle comprises an autonomous truck.
Autonomous trucks are increasingly used for long-haul freight transportation, but ensuring safe and efficient operation in dynamic environments remains a challenge. Existing autonomous trucks often lack advanced systems to dynamically adjust routing based on real-time traffic, weather, or vehicle conditions, leading to inefficiencies and potential safety risks. This invention describes an autonomous truck equipped with a dynamic routing system that continuously evaluates environmental and operational data to optimize travel paths. The truck includes sensors for detecting road conditions, traffic patterns, and weather, as well as onboard diagnostics to monitor vehicle performance. A processing unit analyzes this data to generate updated routing instructions, ensuring the truck avoids hazards, minimizes fuel consumption, and adheres to regulatory constraints. The system may also integrate with external data sources, such as traffic management systems or weather forecasts, to further refine routing decisions. Additionally, the truck may feature adaptive speed control and obstacle avoidance mechanisms to enhance safety during route execution. By dynamically adjusting routes in real time, the invention improves efficiency, reduces downtime, and mitigates risks associated with static or outdated navigation systems.
14. The autonomous vehicle of claim 12 , further comprising: an autonomous driving system configured to generate at least a first portion of the motion planning data for the autonomous vehicle and provide the first portion of the motion planning data to the vehicle control system.
Autonomous vehicles require advanced motion planning systems to navigate complex environments safely and efficiently. A key challenge is ensuring seamless integration between the autonomous driving system and the vehicle control system to execute precise maneuvers. This invention addresses this by enhancing an autonomous vehicle with an autonomous driving system that generates motion planning data and transmits it to the vehicle control system. The autonomous driving system is responsible for creating at least a portion of the motion planning data, which includes trajectory calculations, obstacle avoidance paths, and speed adjustments. This data is then relayed to the vehicle control system, which executes the planned movements by controlling steering, acceleration, and braking. The system ensures real-time coordination between planning and execution, improving responsiveness and safety. By offloading motion planning tasks to a dedicated autonomous driving system, the vehicle control system can focus on precise actuation, reducing latency and enhancing overall performance. This approach is particularly useful in dynamic environments where rapid decision-making is critical, such as urban driving or high-speed scenarios. The invention optimizes the division of labor between planning and control components, leading to more reliable autonomous vehicle operation.
15. The autonomous vehicle of claim 14 , wherein the first portion of the motion planning data is indicative of one or more primary trajectories and one or more stopping trajectories.
Autonomous vehicles rely on motion planning systems to navigate environments safely and efficiently. A key challenge is generating and evaluating multiple potential trajectories to ensure optimal decision-making while avoiding obstacles and adhering to traffic rules. This invention addresses this challenge by enhancing motion planning data to include both primary trajectories and stopping trajectories. The system generates motion planning data that comprises at least two distinct portions. The first portion includes one or more primary trajectories, which represent the vehicle's intended paths under normal driving conditions. These trajectories account for factors such as speed, acceleration, and lane positioning to achieve smooth and efficient navigation. The second portion includes one or more stopping trajectories, which are alternative paths designed to bring the vehicle to a safe stop in response to unexpected obstacles, traffic conditions, or other hazards. These stopping trajectories ensure the vehicle can react quickly and safely to dynamic environments. By integrating both primary and stopping trajectories into the motion planning data, the system enables the autonomous vehicle to proactively evaluate multiple scenarios, improving safety and adaptability. The stopping trajectories provide a fallback option, allowing the vehicle to transition seamlessly from normal operation to a controlled halt if necessary. This approach enhances the vehicle's ability to handle complex driving situations while maintaining compliance with traffic regulations.
16. The autonomous vehicle of claim 15 , further comprising: a computing system configured to generate at least a second portion of the motion planning data for the autonomous vehicle and provide the second portion of the motion planning data to the vehicle control system.
Autonomous vehicles require advanced motion planning systems to navigate complex environments safely and efficiently. A key challenge is ensuring real-time, accurate motion planning that integrates with vehicle control systems to execute maneuvers effectively. This invention addresses this challenge by enhancing an autonomous vehicle with a computing system that generates additional motion planning data. The computing system produces at least a second portion of the motion planning data, which is then transmitted to the vehicle control system. This supplementary data complements the primary motion planning data, enabling more precise and adaptive control of the vehicle's movements. The computing system may operate independently or in conjunction with other onboard systems, ensuring redundancy and improved decision-making. By distributing the motion planning workload, the system enhances reliability and responsiveness, allowing the vehicle to handle dynamic driving scenarios with greater accuracy. This approach optimizes the interaction between planning and execution, improving overall autonomous driving performance.
17. The autonomous vehicle of claim 16 , wherein the autonomous driving system is associated with a first set of vehicle sensors and the computing system is associated with a second set of vehicle sensors, wherein the first set of vehicle sensors is different than the second set of vehicle sensors.
Autonomous vehicles rely on sensor data to navigate and make driving decisions. A challenge arises when different systems within the vehicle, such as the autonomous driving system and the computing system, require distinct sensor inputs. This can lead to redundancy, increased cost, or conflicts in data interpretation. To address this, an autonomous vehicle includes an autonomous driving system and a computing system, each equipped with separate sets of vehicle sensors. The first set of sensors is dedicated to the autonomous driving system, while the second set is used by the computing system. These sensor sets are intentionally different, meaning they may vary in type, placement, or function. For example, the autonomous driving system might use lidar and radar for real-time navigation, while the computing system could rely on cameras and ultrasonic sensors for passenger monitoring or infotainment features. This separation allows each system to operate independently with tailored sensor inputs, improving efficiency and reducing potential interference. The vehicle may also include a communication interface to share data between the systems when necessary, ensuring coordinated operation without sensor overlap. This design optimizes performance by aligning sensor capabilities with specific system requirements.
18. The autonomous vehicle of claim 16 , wherein the second portion of the motion planning data is indicative of one or more objects within a surrounding environment of the autonomous vehicle.
Autonomous vehicles rely on motion planning systems to navigate safely and efficiently. A key challenge is accurately detecting and responding to dynamic objects in the surrounding environment, such as pedestrians, other vehicles, or obstacles, to avoid collisions and ensure smooth operation. To address this, an autonomous vehicle includes a motion planning system that generates motion planning data divided into at least two portions. The first portion contains trajectory data for the vehicle, specifying its intended path and speed. The second portion includes information about one or more objects detected in the vehicle's surrounding environment, such as their positions, velocities, and trajectories. This data allows the vehicle to adjust its planned path in real-time to avoid collisions and navigate safely. The system may also integrate sensor data, such as from cameras, lidar, or radar, to continuously update the object information and refine the motion planning. By separating the trajectory and object data, the system improves computational efficiency and decision-making accuracy, enhancing overall safety and performance.
19. The autonomous vehicle of claim 16 , wherein controlling the first control lane or the second control lane to adjust the motion of the autonomous vehicle based at least in part on the one or more conditions comprises: determining a vehicle action based at least in part on the first portion of the motion planning data, the second portion of the motion planning data, and the one or more conditions; and controlling the first control lane or the second control lane to adjust the motion of the autonomous vehicle based at least in part on the vehicle action.
Autonomous vehicles require precise control systems to navigate complex environments while ensuring safety and efficiency. A key challenge is dynamically adjusting vehicle motion in response to real-time conditions, such as traffic, obstacles, or road changes. This invention addresses this by enhancing an autonomous vehicle's control system to improve motion planning and execution. The system divides motion planning data into at least two portions, each associated with different control lanes. These lanes may correspond to different vehicle subsystems, such as steering, braking, or acceleration. The system monitors one or more conditions, such as sensor inputs, environmental factors, or vehicle state data, to determine the optimal vehicle action. Based on this analysis, the system controls the first or second control lane to adjust the vehicle's motion accordingly. For example, if an obstacle is detected, the system may prioritize braking (second control lane) over steering (first control lane) to ensure a safe stop. The vehicle action is derived from both portions of motion planning data, ensuring coordinated control between subsystems. This approach allows the autonomous vehicle to respond more effectively to dynamic conditions, improving safety and performance.
20. A computer-implemented method, the method comprising: receiving motion planning data for an autonomous vehicle; determining a first control lane of a plurality of control lanes for implementing a motion plan based on the motion planning data, wherein the plurality of control lanes comprise at least the first control lane and a second control lane different than the first control lane, wherein the first control lane is connected with a first set of vehicle actuation systems corresponding to the first control lane, wherein the second control lane is connected with a second set of vehicle actuation systems corresponding to the second control lane, wherein the first set of vehicle actuation systems comprise at least one first actuation system that is not present in the second set of vehicle actuation systems; determining one or more conditions associated with the autonomous vehicle; and controlling the first control lane or the second control lane to adjust a motion of the autonomous vehicle based at least in part on the one or more conditions.
This invention relates to autonomous vehicle motion planning and control systems. The problem addressed is the need for flexible and efficient control of autonomous vehicles by dynamically selecting and utilizing different control lanes, each connected to distinct sets of vehicle actuation systems. The method involves receiving motion planning data for an autonomous vehicle and determining a first control lane from a plurality of control lanes to implement the motion plan. The control lanes are distinct, with each connected to a unique set of vehicle actuation systems. For example, the first control lane is linked to a first set of actuation systems, which includes at least one system not present in the second control lane's set. The method further involves assessing conditions associated with the autonomous vehicle, such as environmental factors or vehicle state, and then controlling either the first or second control lane to adjust the vehicle's motion accordingly. This approach allows the autonomous vehicle to adapt its control strategy based on real-time conditions, optimizing performance and safety by leveraging different actuation systems as needed. The invention ensures that the vehicle can respond dynamically to varying operational scenarios by selecting the most appropriate control lane and its associated actuation systems.
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May 17, 2021
April 19, 2022
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